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1
Unsupervised Aspect Discovery from Online Consumer Reviews
Suleman, Kaheer. - 2014
Abstract: The success of on-line review websites has led to an overwhelming number of on-line consumer reviews. These reviews have become an important tool for consumers when making a decision to purchase a product. This growth has led to the need for applications that enable this information to be presented in a way that is meaningful. These applications often rely on domain specific semantic lexicons which are both expensive and time consuming to make. The following thesis proposes an unsupervised approach for product aspect discovery in on-line consumer reviews. We apply a two step hierarchical clustering process in which we first cluster based on the semantic similarity of the contexts of terms and then on the similarity of the hypernyms of the cluster members. The method also includes a process for assigning class labels to each of the clusters. Finally an experiment showing how the proposed methods can be used to measure aspect based sentiment is performed. The methods proposed in this thesis are evaluated on a set of 157,865 reviews from a major commercial website and found that the two-step clustering process increases cluster F-scores over a single round of clustering. Finally, the proposed methods are compared to a state of the art topic modelling approach by Titov and McDonald (2008).
Keyword: opinion mining; sentiment analysis; term clustering
URL: http://hdl.handle.net/10012/8411
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2
Toward a unifying model for Opinion, Sentiment and Emotion information extraction
In: The 9th International Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-01613403 ; The 9th International Conference on Language Resources and Evaluation, May 2014, Reykjavik, Iceland. pp.3881-3886 ; http://www.lrec-conf.org/proceedings/lrec2014/index.html (2014)
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3
DCU: aspect-based polarity classification for SemEval task 4
In: Wagner, Joachim orcid:0000-0002-8290-3849 , Arora, Piyush orcid:0000-0002-4261-2860 , Cortes, Santiago, Barman, Utsab, Bogdanova, Dasha, Foster, Jennifer orcid:0000-0002-7789-4853 and Tounsi, Lamia (2014) DCU: aspect-based polarity classification for SemEval task 4. In: International Workshop on Semantic Evaluation (SemEval-2014), 23-24 Aug 2014, Dublin, Ireland. ISBN 978-1-941643-24-2 (2014)
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4
Annals of A Model to Compute Degree of Polarity of Review Titles
In: http://www.researchmathsci.org/apamart/apam-v7n1-11.pdf (2014)
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5
The USAGE review corpus for fine-grained, multi-lingual opinion analysis ...
Klinger, Roman. - : Bielefeld University, 2014
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6
The USAGE review corpus for fine-grained, multi-lingual opinion analysis ...
Klinger, Roman. - : Bielefeld University, 2014
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7
The USAGE review corpus for fine-grained, multi-lingual opinion analysis
Klinger, Roman. - : Bielefeld University, 2014
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8
Three Essays on Opinion Mining of Social Media Texts
In: Theses and Dissertations (2014)
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9
Automatic creation of stock market lexicons for sentiment analysis using StockTwits data
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10
Twitris v3: From Citizen Sensing to Analysis, Coordination and Action
In: Amit P. Sheth (2014)
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